This thesis conducts a text and network analysis of criminological files. The specific focus during the research is the field money laundering. The analysis showed the most important concepts present in the text which were classified in eleven different classes. The relationships of those concepts were analysed using ego networks, key entity identification and clustering. Some of the statements given about money laundering could be validated by the findings of this analysis and their interpretation. Specific concepts like banks and organizations as well as foreign subsidiaries were identified. Aggregating these concepts with the statements in chapter 1.4.3 on the circular process of money laundering it can be stated that different organizations and individuals, present in the criminological files, were placing money through different banks, organizations and investments in the legal financial market. At last this thesis tries to validate the benefits of the used tools for the kind of conducted research process. An estimation on ORA's and Automap's applicability for this kind of research is given in the end.